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No-reference stereoscopic image quality assessment based on cyclopean image and enhanced image

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Abstract

In order to effectively evaluate the quality of stereoscopic images, we propose a no-reference stereoscopic image quality assessment (SIQA) method. Firstly, considering the characteristics of binocular fusion, binocular rivalry, and binocular suppression of human visual system, we propose a new color cyclopean image which is suitable for symmetric and asymmetric distortion images. And then, based on the importance of the disparity map, the enhanced image is generated according to the cyclopean image and the disparity map. Next, the natural statistical features are extracted from the enhanced image and the cyclopean image weighted by the gradient of disparity map (named weighted cyclopean image) in the spatial domain. The kurtosis and skewness are extracted from disparity map. Finally, the extracted features are fused and the quality of stereoscopic image is obtained by support vector regression. Experimental results show that the proposed algorithm is superior to most existing objective SIQA methods and can maintain a high degree of consistency with the subjective scores.

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Funding

This study was funded by the National Natural Science Foundation of China (CN) (Grant Nos. 61571325, 61971306).

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Authors and Affiliations

  1. School of Electronic and Information Engineering, Tianjin University, Nankai District, Tianjin, 300072, China

    Sumei Li, Yixiu Ding & Yongli Chang

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  1. Sumei Li
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  2. Yixiu Ding
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Correspondence to Yixiu Ding.

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Li, S., Ding, Y. & Chang, Y. No-reference stereoscopic image quality assessment based on cyclopean image and enhanced image. SIViP 14, 565–573 (2020). https://doi.org/10.1007/s11760-019-01582-6

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  • DOI: https://doi.org/10.1007/s11760-019-01582-6

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